Article,
What to believe: Bayesian methods for data analysis
Trends in cognitive sciences, 14 (7): 293--300 (2010)
Abstract
Although Bayesian models of mind have attracted great
interest from cognitive scientists, Bayesian methods for
data analysis have not. This article reviews several advantages of Bayesian data analysis over traditional null-hypothesis significance testing. Bayesian methods provide
tremendous flexibility for data analytic models and yield
rich information about parameters that can be used
cumulatively across progressive experiments. Because
Bayesian statistical methods can be applied to any data,
regardless of the type of cognitive model (Bayesian or
otherwise) that motivated the data collection, Bayesian
methods for data analysis will continue to be appropriate
even if Bayesian models of mind lose their appeal.
